Synchronization method and related equipment based on double correlation in UAV and satellite communication

Abstract

The present application provides a synchronization method and related equipment based on double correlation in UAV and satellite communication, which relates to the field of satellite communication technology, wherein the method includes: receiving a transmission signal in the UAV and satellite communication, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence; obtaining a local ZC sequence and a local M sequence; performing coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence, and then performing cross-correlation and autocorrelation on the transmission signal on the basis of the coarse synchronization capture, and obtaining a frequency deviation measurement result based on the autocorrelation sequence. The characteristics of the ZC sequence can be used to complete the coarse synchronization capture of the transmission signal, thereby narrowing the range of the synchronization point. Compared with directly obtaining the correlation peak point by cross-correlating the local sequence with the transmission signal, the method can effectively resist the interference of noise in the cross-correlation sequence on the frequency deviation measurement, thereby improving the accuracy of signal synchronization.

Description

Technical Field

[0001] The present application relates to the field of satellite communication technology, and in particular to a synchronization method and related equipment based on double correlation in UAV and satellite communications. Background Art

[0002] In a communication system, the transmission signal consists of a synchronization header and valid data. The synchronization header is a synchronization sequence that distinguishes the beginning of the transmission signal and occupies time domain resources. If the pilot sequence of the synchronization header becomes longer, the pilot sequence used to transmit valid data will become less. Therefore, in order to ensure system transmission efficiency in actual systems, the length of the pilot sequence of the synchronization header will be compressed as much as possible.

[0003] When synchronization is performed at the receiving end under the premise of limited pilot sequence length, due to the characteristics of low-orbit satellite communication system channels such as large Doppler frequency shift, low signal-to-noise ratio and multipath effect, the traditional signal synchronization method for the synchronization head pilot sequence is piecewise conjugate correlation. The anti-noise performance of the piecewise conjugate correlation method in the above scenario is poor, making it difficult to obtain accurate frequency offset measurement results, resulting in low signal synchronization accuracy. Summary of the Invention

[0004] The present application provides a synchronization method and related equipment based on double correlation in drone and satellite communications. When the length of the synchronization head pilot sequence is limited, the synchronization is completed by using the double correlation superposition method, which can more effectively resist noise and obtain accurate frequency deviation measurement results, thereby improving the accuracy of signal synchronization.

[0005] In a first aspect, the present application provides a synchronization method based on double correlation in UAV and satellite communication, which is applied to a receiving end, and the method includes:

[0006] In communication between a UAV and a satellite, a transmission signal is received, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence; and a local ZC sequence and a local M sequence are obtained;

[0007] Performing coarse synchronization capture on a ZC sequence in the transmission signal based on the local ZC sequence to obtain a plurality of position ambiguity points;

[0008] Taking the plurality of position ambiguity points as starting positions, respectively, and conjugating and multiplying the local M sequence with the M sequence of the transmission signal at different starting positions to obtain a cross-correlation sequence;

[0009] Performing autocorrelation conjugate multiplication on the mutual correlation sequence and summing the results to obtain an autocorrelation sequence;

[0010] Frequency offset measurement is performed based on the autocorrelation sequence to obtain a frequency offset measurement result.

[0011] By adopting the above technical solution, the characteristics of the ZC sequence can be used to complete coarse synchronization capture of the transmission signal, thereby narrowing the range of the synchronization point. On the basis of coarse synchronization capture, the transmission signal is subjected to double correlation, namely cross-correlation and autocorrelation, and the frequency offset measurement result is obtained based on the autocorrelation sequence. Compared with directly obtaining the correlation peak point by cross-correlating the local sequence with the transmission signal, this solution can effectively resist the interference of noise in the cross-correlation sequence on the frequency offset measurement, thereby improving the accuracy of signal synchronization.

[0012] Optionally, before performing autocorrelation conjugate multiplication and summing on the mutual correlation sequence to obtain the autocorrelation sequence, the method further includes:

[0013] Performing vector superposition on a plurality of signals adjacent to the cross-correlation sequence to obtain a first cross-correlation sequence;

[0014] The step of performing autocorrelation conjugate multiplication and summing on the mutual correlation sequence to obtain the autocorrelation sequence comprises:

[0015] Perform autocorrelation conjugate multiplication on the first mutual correlation sequence and sum them to obtain an autocorrelation sequence.

[0016] By adopting the above technical solution, vector superposition is performed on several adjacent signals of the mutual correlation sequence, and the obtained first mutual correlation sequence is used as the mutual correlation sequence to complete the subsequent steps. This can reduce the length of the mutual correlation sequence in the form of a two-dimensional matrix, thereby reducing the amount of calculation for subsequent autocorrelation conjugate multiplication and summation.

[0017] Optionally, performing frequency offset measurement based on the autocorrelation sequence to obtain a frequency offset measurement result includes:

[0018] Performing vector superposition on the autocorrelation sequence to obtain a correlation power value, wherein the correlation power value includes an amplitude corresponding to each of the position ambiguity points;

[0019] Finding the position with the maximum amplitude among the relevant power values ​​to obtain the optimal sampling point;

[0020] Frequency offset measurement is performed based on a phase difference between the optimal sampling point and the autocorrelation sequence to obtain a frequency offset measurement result.

[0021] By adopting the above technical solution, the optimal sampling point can be determined by calculating the correlation power value, and then the frequency deviation measurement result can be obtained by the phase difference of the autocorrelation sequence and the optimal sampling point. The optimal sampling point can be obtained near several position ambiguity points, thereby achieving accurate frequency deviation measurement.

[0022] Optionally, performing vector superposition on the autocorrelation sequence to obtain a correlation power value includes:

[0023] Performing vector superposition on the autocorrelation sequence using a correlation power value calculation formula to obtain correlation power values ​​corresponding to the plurality of position ambiguity points;

[0024] The relevant power value calculation formula is:

[0025]

[0026] Among them, p is the value of the several position ambiguity points; Xcorr_avg(p) is the correlation power value corresponding to the several position ambiguity points; LP is the length of the autocorrelation sequence; le is the value of the length of the autocorrelation sequence; corr_seq is the autocorrelation sequence; P is the number of the several position ambiguity points.

[0027] By adopting the above technical solution, the relevant power value corresponding to each position ambiguity point can be accurately obtained according to the relevant power value calculation formula, which facilitates the subsequent finding of the accurate optimal sampling point.

[0028] Optionally, obtaining the position of the maximum amplitude in the correlation power values ​​to obtain the optimal sampling point includes: obtaining the position of the maximum amplitude in the correlation power values ​​using a maximum amplitude calculation formula to obtain the optimal sampling point;

[0029] The maximum amplitude calculation formula is:

[0030] [maxV, maxPOS]=Max(Xcorr_avg(p)), p=1, 2,...,P;

[0031] Among them, p is the value of the said several position ambiguity points; Xcorr_avg(p) is the said correlation power value; maxPOS is the position of the maximum amplitude in the said correlation power value, and P is the number of the said several position ambiguity points.

[0032] By adopting the above technical solution, the position with the largest amplitude in the relevant power values ​​is obtained through traversal screening, and the accurate optimal sampling point can be found, thereby improving the accuracy of subsequent frequency deviation measurement results.

[0033] Optionally, performing frequency offset measurement based on a phase difference between the optimal sampling position and the autocorrelation sequence to obtain a frequency offset measurement result includes:

[0034] Calculating the correlation vector corresponding to the optimal sampling point;

[0035] Calculating a phase difference of the autocorrelation sequence based on the correlation vector;

[0036] A frequency offset measurement result is calculated based on the phase difference of the autocorrelation sequence.

[0037] By adopting the above technical solution, according to the obtained optimal sampling point, the autocorrelation sequence is returned to calculate the phase difference before and after the sequence, thereby obtaining the frequency offset measurement result, which can reduce the interference of the cross-correlation sequence on the frequency offset measurement result and improve the accuracy and reliability of the frequency offset measurement result.

[0038] Optionally, a correlation vector calculation formula is used to calculate the correlation vector corresponding to the optimal sampling point;

[0039] The correlation vector calculation formula is:

[0040] corr_sig=corr_seq(maxPOS,:);

[0041] Wherein, corr_sig is the correlation vector corresponding to the optimal sampling point; corr_seq(maxPOS,:) is the autocorrelation sequence corresponding to the optimal sampling point;

[0042] The calculating the phase difference of the autocorrelation sequence based on the correlation vector includes:

[0043] Based on the correlation vector, a phase angle formula is used to calculate the phase difference of the autocorrelation sequence;

[0044] The phase angle formula is:

[0045]

[0046] Wherein, theta is the phase difference of the autocorrelation sequence, angle is the phase angle calculation function; LP is the length of the autocorrelation sequence; le is the value of half the length of the autocorrelation sequence; corr_sig is the correlation vector corresponding to the optimal sampling point;

[0047] The calculating the frequency offset measurement result based on the phase difference of the autocorrelation sequence includes:

[0048] Calculating a frequency deviation measurement result using a frequency deviation calculation formula based on the phase difference of the autocorrelation sequence;

[0049] The frequency deviation calculation formula is:

[0050]

[0051] Among them, foe is the frequency offset measurement result; theta is the phase difference of the autocorrelation sequence; LP is the length of the autocorrelation sequence; OP is the number of signal superpositions of the autocorrelation sequence; and fs is the sampling frequency of the transmission signal.

[0052] By adopting the above technical solution, based on the optimal sampling point and the autocorrelation sequence, the frequency offset measurement result is obtained by obtaining the phase difference, which can improve the accuracy of the frequency offset measurement result and achieve accurate synchronization of the transmission signal.

[0053] In a second aspect, the present application provides a synchronization device based on double correlation in communication between a drone and a satellite, which is applied to a receiving end, and the device includes:

[0054] A transmission signal receiving module is used to receive a transmission signal during communication between the UAV and the satellite, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence;

[0055] A local sequence acquisition module is used to obtain local ZC sequences and local M sequences;

[0056] A coarse synchronization capture module, configured to perform coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence to obtain a plurality of position ambiguity points;

[0057] a mutual correlation sequence calculation module, configured to use the plurality of position ambiguity points as starting positions, and conjugate-multiply the local M sequence with the M sequences of the transmission signals at different starting positions to obtain a mutual correlation sequence;

[0058] The autocorrelation sequence calculation module is used to perform autocorrelation conjugate multiplication and summation on the mutual correlation sequence to obtain an autocorrelation sequence; the frequency offset measurement result calculation module is used to perform frequency offset measurement based on the autocorrelation sequence to obtain a frequency offset measurement result.

[0059] In a third aspect, the present application provides a computer storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the above methods.

[0060] In a fourth aspect, the present application provides an electronic device comprising a processor, a memory and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any one of the above methods.

[0061] In summary, the beneficial effects brought about by the technical solution of this application include:

[0062] The characteristics of the ZC sequence can be used to complete the coarse synchronization capture of the transmission signal, thereby narrowing the range of the synchronization point. Based on the coarse synchronization capture, the transmission signal is subjected to double correlation and autocorrelation, and the frequency offset measurement result is obtained based on the autocorrelation sequence. Compared with directly obtaining the correlation peak point by cross-correlating the local sequence with the transmission signal, the proposed method can effectively resist the interference of noise in the cross-correlation sequence on the frequency offset measurement, thereby improving the accuracy of signal synchronization. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flowchart of a synchronization method based on double correlation in UAV and satellite communication provided by an embodiment of the present application;

[0064] Figure 2 is a waveform diagram of a buffer compensation signal provided in an embodiment of the present application;

[0065] Figure 3 This is a schematic diagram of the steps of superimposing a mutual correlation sequence provided in an embodiment of the present application;

[0066] Figure 4 This is a schematic diagram of the steps for obtaining an autocorrelation sequence provided in an embodiment of the present application;

[0067] Figure 5 This is a flow chart of another synchronization method based on double correlation in UAV and satellite communication provided by an embodiment of the present application;

[0068] Figure 6 This is a schematic diagram of the steps for obtaining relevant power values ​​provided in an embodiment of the present application;

[0069] Figure 7 This is a simulation result diagram of a correlation peak comparison provided by an embodiment of the present application;

[0070] Figure 8 This is another simulation result diagram of correlation peak comparison provided by an embodiment of the present application;

[0071] Figure 9 This is another simulation result diagram of correlation peak comparison provided by an embodiment of the present application;

[0072] Figure 10 This is a schematic diagram of the steps of fine capture provided by an embodiment of the present application;

[0073] Figure 11 This is a structural diagram of a synchronization device based on double correlation in UAV and satellite communication provided by an embodiment of the present application;

[0074] Figure 12 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0075] Explanation of the accompanying drawings: 10. Transmission signal receiving module; 20. Local sequence acquisition module; 30. Coarse synchronization capture module; 40. Cross-correlation sequence calculation module; 50. Autocorrelation sequence calculation module; 60. Frequency deviation measurement result calculation module; 1200. Electronic device; 1201. Processor; 1202. Communication bus; 1203. User interface; 1204. Network interface; 1205. Memory. DETAILED DESCRIPTION

[0076] In order to enable people skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0077] In the description of the embodiments of this application, words such as "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0078] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0079] See Figure 1 , which is a flow chart of a dual-correlation-based synchronization method for drone and satellite communications, provided in an embodiment of the present application. This method can be implemented using a computer program, a single-chip microcomputer, or run on a dual-correlation-based synchronization device for drone and satellite communications based on a von Neumann architecture. The computer program can be integrated into an application or run as a standalone tool application. This embodiment of the present application uses the receiving end as an example to provide a detailed description of the specific steps of the dual-correlation-based synchronization method for drone and satellite communications.

[0080] It should also be understood that the embodiments of the present application only take the receiving end as an example. Between two signal transmission entities, the receiving end may include either of the two entities. The receiving end may be a satellite or a drone. For example, if the signal is transmitted from a drone to a satellite, the satellite serves as the receiving end.

[0081] S101, in the communication between the UAV and the satellite, a transmission signal is received, and the synchronization header of the transmission signal includes a ZC sequence and an M sequence.

[0082] It should be understood that the communication between the drone and the satellite in the embodiments of the present application can also be the communication between the drone's built-in communication device and the satellite, which can be associated with the communication between other devices equipped with communication devices and satellites. Therefore, the communication between the drone and the satellite mentioned in the embodiments of the present application should also cover the communication between the communication device and the satellite.

[0083] The transmission signal is the actual communication signal between the drone and the satellite. The synchronization header of the transmission signal consists of the ZC sequence and the M sequence. The M sequence is the abbreviation of the longest linear feedback shift register sequence and is the most basic PN sequence used in communication systems. The ZC sequence is a CAZAC sequence with constant amplitude and zero autocorrelation. The ZC sequence has good autocorrelation and cross-correlation in terms of synchronization, so it can be well applied in Orthogonal Frequency Division Multiplexing (OFDM) technology.

[0084] It is understandable that the synchronization header will occupy time domain resources, so the pilot sequence length of the synchronization header cannot be too long. At the same time, in order to ensure noise resistance, the pilot sequence length of the synchronization header cannot be too short. The present application provides a possible synchronization header pilot sequence length value, which is 32, 64, 1024, and 4096. For example, the pilot sequence length of the synchronization header is 1024 sampling points, and the synchronization header can be divided into a ZC sequence of 512 sampling points and an M sequence of 512 sampling points.

[0085] S102: Obtain a local ZC sequence and a local M sequence.

[0086] The local ZC sequence and the local M sequence are sequences stored locally at the receiving end. It can be understood that the local ZC sequence and the local M sequence are known sequences corresponding to the synchronization header of the transmission signal, and can also be obtained through a memory or a data cloud.

[0087] S103 , performing coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence to obtain a number of position ambiguity points.

[0088] Coarse synchronization capture uses a timing synchronization algorithm to estimate the transmission signal. Due to the Doppler frequency shift and low signal-to-noise ratio in low-orbit satellite communication systems, noise has a significant impact on timing synchronization, resulting in several position ambiguity points, which are uncertain sampling positions.

[0089] In a feasible coarse synchronization acquisition method, the ZC sequence features sharp cyclic autocorrelation peaks and zero sidelobes. These excellent properties can improve synchronization in multipath fading channels. Furthermore, its peak-to-average ratio and constant modulus make it widely used in synchronization algorithms, enhancing system timing accuracy. Therefore, a timing metric function can be used to refine coarse synchronization acquisition based on the structural characteristics of the ZC sequence and its correlation with the local ZC sequence.

[0090] The timing metric function is:

[0091]

[0092] Where r(n) is the transmission signal, Z * (n) is the complex conjugate of the local ZC sequence. From the correlation, it can be seen that d corresponding to the peak of M(d) is the timing position.

[0093] Near the accurate timing point, the timing metric function is very sharp, and the sampling point corresponding to the timing position is the position ambiguity point.

[0094] S104 , using several position ambiguity points as starting positions, and conjugating and multiplying the local M sequence with the M sequence of the transmission signal at different starting positions to obtain a cross-correlation sequence.

[0095] See Figure 2 , which is a schematic diagram of the steps for generating a cross-correlation sequence provided in an embodiment of the present application. After coarse synchronization capture using the ZC sequence, several position ambiguities still exist, but the most accurate position among the several position ambiguities still needs to be determined. The local M sequence is conjugate-multiplied with the M sequence of the transmitted signal to obtain the cross-correlation sequence using the following specific formula:

[0096] hloc(p,:) noise =b noise (IPoint*m+p)*h * (m),p=1,2…P,m=1,2…M;

[0097] Where hloc is the cross-correlation sequence in two-dimensional matrix form, the suffix noise is used to indicate that the cross-correlation sequence contains noise, and b noise is the transmission signal with noise, IPoint is the oversampling multiple of the chip, h is the local M sequence with the same length as the M sequence, h * (m) is the conjugate value of the m-th position of the local M sequence, p is the value of several position ambiguity points, P is the number of several position ambiguity points, and M is the value of the local M sequence.

[0098] The above formula means that the M transmission signals starting from the p-th position ambiguity point are point-multiplied by the h sequence in the local M sequence with a local length of M to obtain the cross-correlation sequence.

[0099] In an optional embodiment, vector superposition is performed on several signals adjacent to the mutual correlation sequence to obtain a first mutual correlation sequence.

[0100] See Figure 3 , a schematic diagram of the steps for superimposing a mutual correlation sequence provided in an embodiment of the present application, wherein several signal vectors adjacent to the mutual correlation sequence are superimposed to obtain a first mutual correlation sequence of shortened length. The number of signal vectors superimposed is OP, and the value of OP is limited by the ADC sampling rate. Because the scanning accuracy of the code chip is the accuracy of receiver synchronization, the higher the ADC oversampling rate, the larger the value of OP, the lower the subsequent computational complexity, and the system performance is almost unchanged, but the cost is also higher. For example, if the length of the mutual correlation sequence M = 512 and OP = 4, the length of the obtained first mutual correlation sequence CM = 128.

[0101] The first mutual correlation sequence formula is used to perform vector superposition on several signals adjacent to the mutual correlation sequence to obtain the first mutual correlation sequence. The first mutual correlation sequence formula is as follows:

[0102] ph=1:CM; index1=(ph-1)*OP+1:ph*OP;

[0103] h_Cadd(p,:)=hloc(p,index1), p=1, 2...P;

[0104] Wherein, CM is the length of the first mutual correlation sequence, ph is the value assigned to the length of the first mutual correlation sequence, and h_Cadd(p,:) is the first mutual correlation sequence.

[0105] The purpose of the first mutual correlation sequence is to reduce the length of the mutual correlation sequence in the form of a two-dimensional matrix, so as to reduce the computational complexity of subsequent synchronization.

[0106] S105 , performing autocorrelation conjugate multiplication on the mutual correlation sequence and summing the results to obtain an autocorrelation sequence.

[0107] Autocorrelation, also known as serial correlation, refers to the degree of correlation between the values ​​of a time series at any two different moments. It is used to describe the dependency of the value of a signal at one moment on the value at another moment.

[0108] In an optional embodiment, autocorrelation conjugate multiplication is performed on the first mutual correlation sequence and the sum is calculated to obtain an autocorrelation sequence.

[0109] See Figure 4, is a schematic diagram of a step for obtaining an autocorrelation sequence provided in an embodiment of the present application, wherein an autocorrelation function is used to perform autocorrelation conjugate multiplication and addition on a first mutual correlation sequence to obtain an autocorrelation sequence, wherein the autocorrelation function is as follows: index2=LP-le+1:CM, index3=1:CM-LP+le, p=1:P, le=1:LP;

[0110] corr_seq(p,le)=∑h_Cadd(p,index2)*h_Cadd * (p,index3);

[0111] Where LP is the target length of the autocorrelation sequence, corr_seq is the autocorrelation sequence, and h_Cadd is * is the conjugate value of the p-th position of the first cross-correlation sequence.

[0112] S106: Perform frequency offset measurement based on the autocorrelation sequence to obtain a frequency offset measurement result.

[0113] Frequency offset measurement is performed based on the autocorrelation sequence, and the most accurate position sampling point is obtained from several position ambiguity points. Frequency offset measurement is performed based on the most accurate position sampling point and the autocorrelation sequence to obtain the frequency offset measurement result, thereby achieving synchronization.

[0114] In the steps of the synchronization method based on double correlation in drone and satellite communication in another embodiment of the present application, the steps of how to perform frequency deviation measurement based on the autocorrelation sequence are described in detail, and the difference in effect between the double correlation synchronization method provided by the present application and the existing synchronization method is compared to prove the effectiveness of the present application in practical application.

[0115] See Figure 5 , which is a flow chart of another synchronization method based on double correlation in UAV and satellite communication provided in an embodiment of the present application, the method includes steps S201 to S208.

[0116] S201, in the communication between the UAV and the satellite, a transmission signal is received, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence.

[0117] S202: Acquire a local ZC sequence and a local M sequence.

[0118] S203 , performing coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence to obtain a number of position ambiguity points.

[0119] S204 , using several position ambiguity points as starting positions, and conjugating and multiplying the local M sequence with the M sequence of the transmission signal at different starting positions to obtain a cross-correlation sequence.

[0120] S205 , performing autocorrelation conjugate multiplication on the mutual correlation sequence and summing the results to obtain an autocorrelation sequence.

[0121] Steps S201 to S205 have been described in detail in steps S101 to S105 of the above embodiment and will not be repeated here.

[0122] S206 , performing vector superposition on the autocorrelation sequence to obtain a correlation power value, where the correlation power value includes an amplitude corresponding to each position ambiguity point.

[0123] See Figure 6 , which is a schematic diagram of the steps for obtaining the correlation power value provided in an embodiment of the present application. The correlation power value of a single position ambiguity point is the vector superposition result of the autocorrelation sequence near this position ambiguity point. The correlation power values ​​corresponding to several position ambiguity points are obtained by the same method.

[0124] In one embodiment, a correlation power value calculation formula is used to perform vector superposition on the autocorrelation sequence to obtain correlation power values ​​corresponding to a number of position ambiguity points;

[0125] The relevant power value calculation formula is:

[0126]

[0127] Among them, p is the value of several position ambiguity points; Xcorr_avg(p) is the correlation power value corresponding to several position ambiguity points; LP is the length of the autocorrelation sequence; le is the value of the length of the autocorrelation sequence; corr_seq is the autocorrelation sequence; P is the number of several position ambiguity points.

[0128] S207, finding the position with the maximum amplitude in the relevant power values ​​to obtain the optimal sampling point.

[0129] In one embodiment, a maximum amplitude calculation formula is used to obtain the position of the maximum amplitude in the relevant power values ​​to obtain the optimal sampling point;

[0130] The maximum amplitude calculation formula is:

[0131] [maxV, maxPOS]=Max(Xcorr_avg(p)), p=1, 2,...,P;

[0132] Among them, p is the value of several position ambiguity points; Xcorr_avg(p) is the correlation power value; maxPOS is the position with the largest amplitude in the correlation power value, and P is the number of several position ambiguity points.

[0133] From several related power values, select the position with the largest amplitude among the related power values. The position with the largest amplitude corresponds to the best sampling point.

[0134] See Figure 7 、 Figure 8 as well as Figure 9 , Figure 7 This is a simulation result diagram of a correlation peak comparison provided in an embodiment of the present application. Figure 8 This is another simulation result diagram of correlation peak comparison provided in an embodiment of the present application. Figure 9 This is another simulation result diagram of correlation peak comparison provided in an embodiment of the present application. Figure 7 The simulation environment is a white noise channel with low signal-to-noise ratio (SNR=-4). Figure 8 The simulation environment is a white noise channel with a very low signal-to-noise ratio (SNR=-9). Figure 9 The simulation environment is a two-path channel with a very low signal-to-noise ratio (SNR=-9). From the simulation diagram, we can clearly see that:

[0135] Figure 7 In the case of a low signal-to-noise ratio, the amplitude of the correlation peak point of the synchronization method based on double correlation provided by the embodiment of the present application is greater than that of the traditional correlation method, which can reduce the requirement for the decision threshold when searching for the correlation peak point, and thus can quickly achieve synchronization when the pilot length of the synchronization header is limited;

[0136] Figure 8 In the case of a very low signal-to-noise ratio, the difference between the amplitude of the side-correlation power values ​​outside the correlation peak point of the traditional correlation method and the amplitude at the correlation peak point becomes smaller, that is, the side-correlation amplitude affects the determination of the correlation peak point. However, the synchronization method based on double correlation provided in the embodiment of the present application has a lower side-correlation power value, while the amplitude at the correlation peak point is greater than the amplitude at the correlation peak point of the traditional correlation method, indicating that the method provided in the present application can quickly and accurately achieve the acquisition of the correlation peak point (optimal sampling point);

[0137] Figure 9 In the case of a very low signal-to-noise ratio, the amplitude difference between the two correlation peak points obtained by the traditional correlation method in the two-path channel is small, making it difficult to determine the accurate optimal sampling point. However, the amplitudes of the two correlation peak points of the synchronization method based on double correlation provided in the embodiment of the present application are significantly different, indicating that the method of the embodiment of the present application can improve the accuracy of obtaining the optimal sampling point.

[0138] S208 , performing frequency offset measurement based on the phase difference between the optimal sampling point and the autocorrelation sequence, and calculating a frequency offset measurement result.

[0139] S2081, calculate the correlation vector corresponding to the optimal sampling point.

[0140] Use the correlation vector calculation formula to calculate the correlation vector corresponding to the optimal sampling point;

[0141] The correlation vector calculation formula is:

[0142] corr_sig=corr_seq(maxPOS,:);

[0143] Among them, corr_sig is the correlation vector corresponding to the optimal sampling point; corr_seq(maxPOS,:) is the autocorrelation sequence corresponding to the optimal sampling point.

[0144] S2082: Calculate the phase difference of the autocorrelation sequence based on the correlation vector.

[0145] Based on the correlation vector, the phase angle formula is used to calculate the phase difference of the autocorrelation sequence;

[0146] The phase angle formula is:

[0147]

[0148] Where theta is the phase difference of the autocorrelation sequence, angle is the phase angle calculation function, LP is the length of the autocorrelation sequence, le is the value of half the length of the autocorrelation sequence, and corr_sig is the correlation vector corresponding to the optimal sampling point.

[0149] S2083: Calculate a frequency offset measurement result based on the phase difference of the autocorrelation sequence.

[0150] Based on the phase difference of the autocorrelation sequence, the frequency offset measurement result is calculated using the frequency offset calculation formula;

[0151] The frequency deviation calculation formula is:

[0152]

[0153] Where foe is the frequency offset measurement result; theta is the phase difference of the autocorrelation sequence; LP is the length of the autocorrelation sequence; OP is the number of signal superpositions of the autocorrelation sequence; and fs is the sampling frequency of the transmission signal.

[0154] In one embodiment, see Figure 10 , is a schematic diagram of a fine capture step provided in an embodiment of the present application, which describes in detail the various steps of fine capture after coarse capture, and based on the description of the above embodiment, the summary formula is as follows:

[0155] Step 1: Cross-correlate the transmitted sequence with the local M sequence to obtain the cross-correlation sequence hloc. The specific formula is:

[0156] hloc(p,:) noise =b noise (IPoint*m+p)*h *(m),p=1,2…P,m=1,2…M;

[0157] Step 2: Perform vector superposition on several adjacent signals of the cross-correlation sequence to obtain the first cross-correlation sequence h_Cadd. The specific formula is:

[0158] ph=1:CM; index1=(ph-1)*OP+1:ph*OP;

[0159] h_Cadd(p,:)=hloc(p,index1), p=1, 2...P;

[0160] In the actual processing process, the third step and the fourth step can be linked together for processing. In the third step, the first mutual correlation sequence is autocorrelated to obtain the autocorrelation sequence corr_seq. In the fourth step, the autocorrelation sequence vectors are superimposed to obtain the correlation power value Xcorr_avg. The specific formula is:

[0161] index2=LP-le+1:CM, index3=1:CM-LP+le, p=1:P, le=1:LP;

[0162] corr_seq(p,le)=∑h_Cadd(p,index2)*h_Cadd * (p,index3);

[0163]

[0164] Step 5: Find the position maxPOS with the largest amplitude among the relevant power values. The specific formula is:

[0165] [maxV, maxPOS]=Max(Xcorr_avg(p)), p=1, 2,...,P;

[0166] Step 6: Obtain the correlation vector corr_sig of the optimal sampling point based on the position with the maximum amplitude, and use the phase difference before and after the autocorrelation sequence to measure the frequency offset and obtain the frequency offset measurement result foe.

[0167] corr_sig=corr_seq(maxPOS,:);

[0168]

[0169] The specific interpretation of the above formula has been described in detail in the above embodiments and will not be repeated here.

[0170] Through the above technical solution, the characteristics of the ZC sequence can be used to complete the coarse synchronization capture of the transmission signal, thereby narrowing the range of the synchronization point. On the basis of the coarse synchronization capture, the transmission signal is subjected to double correlation, namely cross-correlation and autocorrelation, and the frequency offset measurement result is obtained based on the autocorrelation sequence. Compared with directly obtaining the correlation peak point by cross-correlating the local sequence with the transmission signal, this solution can effectively resist the interference of noise in the cross-correlation sequence on the frequency offset measurement, thereby improving the accuracy of signal synchronization.

[0171] The following are system embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the system embodiments of the present application, please refer to the method embodiments of the present application.

[0172] See Figure 11 , which shows a schematic diagram of the structure of a dual-correlation synchronization device for drone-satellite communications, provided by an exemplary embodiment of the present application. This device can be implemented as all or part of a device through software, hardware, or a combination of both. The device includes a transmission signal receiving module 10, a local sequence acquisition module 20, a coarse synchronization acquisition module 30, an autocorrelation sequence calculation module 50, and a frequency offset measurement result calculation module 60.

[0173] The transmission signal receiving module 10 is used to receive the transmission signal in the communication between the UAV and the satellite. The synchronization header of the transmission signal includes a ZC sequence and an M sequence.

[0174] A local sequence acquisition module 20 is used to acquire a local ZC sequence and a local M sequence;

[0175] A coarse synchronization capture module 30 is used to perform coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence to obtain a number of position ambiguity points;

[0176] The cross-correlation sequence calculation module 40 is configured to use a plurality of position ambiguity points as starting positions, and conjugate-multiply the local M sequence with the M sequence of the transmission signal at different starting positions to obtain a cross-correlation sequence;

[0177] The autocorrelation sequence calculation module 50 is used to perform autocorrelation conjugate multiplication and summation on the mutual correlation sequence to obtain the autocorrelation sequence; the frequency offset measurement result calculation module 60 is used to perform frequency offset measurement based on the autocorrelation sequence to obtain the frequency offset measurement result.

[0178] Optionally, the mutual correlation sequence calculation module 40 further includes a first mutual correlation sequence calculation module 41,

[0179] The first mutual correlation sequence calculation module 41 is configured to perform vector superposition on a plurality of signals adjacent to the mutual correlation sequence to obtain a first mutual correlation sequence; and perform autocorrelation conjugate multiplication and summation on the mutual correlation sequence to obtain an autocorrelation sequence, including: performing autocorrelation conjugate multiplication and summation on the first mutual correlation sequence to obtain an autocorrelation sequence.

[0180] Optionally, the frequency offset measurement result calculation module 60 further includes an optimal sampling point acquisition module 61 .

[0181] The optimal sampling point acquisition module 61 is used to perform vector superposition on the autocorrelation sequence to obtain the correlation power values ​​corresponding to several position ambiguity points; obtain the position with the maximum amplitude in the correlation power value to obtain the optimal sampling point; and perform frequency deviation measurement based on the phase difference between the optimal sampling point and the autocorrelation sequence to obtain the frequency deviation measurement result.

[0182] Optionally, the optimal sampling point acquisition module 61 further includes a correlation power value calculation unit 611 , a maximum amplitude position screening unit 612 , and a frequency deviation measurement unit 613 .

[0183] The correlation power value calculation unit 611 is used to perform vector superposition on the autocorrelation sequence using the correlation power value calculation formula to obtain correlation power values ​​corresponding to a number of position ambiguity points;

[0184] The relevant power value calculation formula is:

[0185]

[0186] Among them, Xcorr_avg(p) is the correlation power value corresponding to several position ambiguity points; LP is the length of the autocorrelation sequence; le is the value of the length of the autocorrelation sequence; corr_seq is the autocorrelation sequence; P is the number of several position ambiguity points.

[0187] The maximum amplitude position screening unit 612 is used to use the maximum amplitude calculation formula to find the position of the maximum amplitude in the relevant power value to obtain the optimal sampling point;

[0188] The maximum amplitude calculation formula is:

[0189] [maxV, maxPOS]=Max(Xcorr_avg(p)), p=1, 2,...,P;

[0190] Among them, p is the value of several position ambiguity points; Xcorr_avg(p) is the correlation power value; maxPOS is the position with the largest amplitude in the correlation power value, and P is the number of several position ambiguity points.

[0191] The frequency offset measurement unit 613 is configured to calculate a correlation vector corresponding to the optimal sampling point; calculate a phase difference of an autocorrelation sequence based on the correlation vector; and calculate a frequency offset measurement result based on the phase difference of the autocorrelation sequence.

[0192] Optionally, the frequency offset measurement unit 613 further includes a correlation vector calculation unit 6131 , a phase difference calculation unit 6132 and a frequency offset calculation unit 6133 .

[0193] A correlation vector calculation unit 6131 is configured to calculate the correlation vector corresponding to the optimal sampling point using a correlation vector calculation formula;

[0194] The correlation vector calculation formula is:

[0195] corr_sig=corr_seq(maxPOS,:);

[0196] Among them, corr_sig is the correlation vector corresponding to the optimal sampling point; corr_seq(maxPOS,:) is the autocorrelation sequence corresponding to the optimal sampling point.

[0197] A phase difference calculation unit 6132 is configured to calculate the phase difference of the autocorrelation sequence based on the correlation vector using a phase angle formula;

[0198] The phase angle formula is:

[0199]

[0200] Where theta is the phase difference of the autocorrelation sequence, angle is the phase angle calculation function, LP is the length of the autocorrelation sequence, le is the value of half the length of the autocorrelation sequence, and corr_sig is the correlation vector corresponding to the optimal sampling point.

[0201] A frequency offset calculation unit 6133 is configured to calculate a frequency offset measurement result based on a phase difference of an autocorrelation sequence using a frequency offset calculation formula;

[0202] The frequency deviation calculation formula is:

[0203]

[0204] Where foe is the frequency offset measurement result; theta is the phase difference of the autocorrelation sequence; LP is the length of the autocorrelation sequence; OP is the number of signal superpositions of the autocorrelation sequence; and fs is the sampling frequency of the transmission signal.

[0205] The present application also provides a computer storage medium that can store multiple instructions, which are suitable for being loaded and executed by a processor as described above. Figures 1-11The synchronization method based on double correlation in the UAV and satellite communication of the embodiment shown in the figure can be specifically implemented by referring to Figures 1-11 The detailed description of the illustrated embodiment will not be repeated here.

[0206] See Figure 12 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 12 As shown, the electronic device 1200 may include: at least one processor 1201 , at least one network interface 1204 , a user interface 1203 , a memory 1205 , and at least one communication bus 1202 .

[0207] The communication bus 1202 is used to implement the connection and communication between these components.

[0208] The user interface 1203 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1203 may also include a standard wired interface and a wireless interface.

[0209] The network interface 1204 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0210] The processor 1201 may include one or more processing cores. The processor 1201 utilizes various interfaces and circuits to connect various components within the server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 1205, and by accessing data stored in the memory 1205, the processor 1201 performs various server functions and processes data. Optionally, the processor 1201 may be implemented using at least one hardware form selected from the group consisting of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 1201 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; and the modem is responsible for handling wireless communications. It is understood that the modem may not be integrated into the processor 1201 and may be implemented separately on a single chip.

[0211] Among them, the memory 1205 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 1205 includes a non-transitory computer-readable storage medium. The memory 1205 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1205 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1205 may also be optionally at least one storage device located away from the aforementioned processor 1201. As Figure 12 As shown, the memory 1205 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a synchronization method based on double correlation in communication between a UAV and a satellite.

[0212] exist Figure 12 In the electronic device 1200 shown, the user interface 1203 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1201 can be used to call an application stored in the memory 1205 for a synchronization method based on double correlation in communication between a drone and a satellite. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0213] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0214] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0215] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0216] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of the devices or units can be electrical or other forms.

[0217] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0218] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0219] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0220] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A synchronization method based on double correlation in UAV and satellite communication, characterized in that: Applied to a receiving end, the method includes: In communication between a UAV and a satellite, a transmission signal is received, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence; Get the local ZC sequence and local M sequence; Performing coarse synchronization capture on a ZC sequence in the transmission signal based on the local ZC sequence to obtain a plurality of position ambiguity points; Taking the plurality of position ambiguity points as starting positions, respectively, and conjugating and multiplying the local M sequence with the M sequence of the transmission signal at different starting positions to obtain a cross-correlation sequence; Performing autocorrelation conjugate multiplication on the mutual correlation sequence and summing the results to obtain an autocorrelation sequence; Frequency offset measurement is performed based on the autocorrelation sequence to obtain a frequency offset measurement result.

2. The method according to claim 1, characterized in that Before performing autocorrelation conjugate multiplication and summing on the mutual correlation sequence to obtain the autocorrelation sequence, the method further includes: Performing vector superposition on a plurality of signals adjacent to the cross-correlation sequence to obtain a first cross-correlation sequence; The step of performing autocorrelation conjugate multiplication and summing on the mutual correlation sequence to obtain the autocorrelation sequence comprises: Perform autocorrelation conjugate multiplication on the first mutual correlation sequence and sum them to obtain an autocorrelation sequence.

3. The method according to claim 1, characterized in that The performing frequency offset measurement based on the autocorrelation sequence to obtain a frequency offset measurement result includes: Performing vector superposition on the autocorrelation sequence to obtain a correlation power value, wherein the correlation power value includes an amplitude corresponding to each of the position ambiguity points; Finding the position with the maximum amplitude among the relevant power values ​​to obtain the optimal sampling point; Frequency offset measurement is performed based on a phase difference between the optimal sampling point and the autocorrelation sequence to obtain a frequency offset measurement result.

4. The method according to claim 3, characterized in that The performing vector superposition on the autocorrelation sequence to obtain a correlation power value includes: Performing vector superposition on the autocorrelation sequence using a correlation power value calculation formula to obtain correlation power values ​​corresponding to the plurality of position ambiguity points; The relevant power value calculation formula is: ,le=1,2,…,LP,p=1,2,…,P; Among them, p is the value of the several position ambiguity points; Xcorr_avg(p) is the correlation power value corresponding to the several position ambiguity points; LP is the length of the autocorrelation sequence; le is the value of the length of the autocorrelation sequence; corr_seq is the autocorrelation sequence; P is the number of the several position ambiguity points.

5. The method according to claim 3, characterized in that The step of obtaining the position with the maximum amplitude in the correlation power value to obtain the optimal sampling point includes: Use the maximum amplitude calculation formula to find the position of the maximum amplitude in the relevant power value to obtain the optimal sampling point; The maximum amplitude calculation formula is: [maxV, maxPOS]=Max(Xcorr_avg(p)), p=1, 2,…,P; Among them, p is the value of the several position ambiguity points; Xcorr_avg(p) is the correlation power value corresponding to the several position ambiguity points; maxPOS is the position with the largest amplitude in the correlation power value; P is the number of the several position ambiguity points.

6. The method according to claim 3, characterized in that The performing frequency offset measurement based on the phase difference between the optimal sampling point and the autocorrelation sequence to obtain a frequency offset measurement result includes: Calculating the correlation vector corresponding to the optimal sampling point; Calculating a phase difference of the autocorrelation sequence based on the correlation vector; A frequency offset measurement result is calculated based on the phase difference of the autocorrelation sequence.

7. The method according to claim 6, characterized in that The calculating the correlation vector corresponding to the optimal sampling point includes: Calculate the correlation vector corresponding to the optimal sampling point using a correlation vector calculation formula; The correlation vector calculation formula is: corr_sig=corr_seq(maxPOS,:); Wherein, corr_sig is the correlation vector corresponding to the optimal sampling point; corr_seq(maxPOS,:) is the autocorrelation sequence corresponding to the optimal sampling point; The calculating the phase difference of the autocorrelation sequence based on the correlation vector includes: Based on the correlation vector, a phase angle formula is used to calculate the phase difference of the autocorrelation sequence; The phase angle formula is: ,le=1,2,…,LP / 2; Wherein, theta is the phase difference of the autocorrelation sequence, angle is the phase angle calculation function; LP is the length of the autocorrelation sequence; le is the value of half the length of the autocorrelation sequence; corr_sig is the correlation vector corresponding to the optimal sampling point; The calculating the frequency offset measurement result based on the phase difference of the autocorrelation sequence includes: Calculating a frequency deviation measurement result using a frequency deviation calculation formula based on the phase difference of the autocorrelation sequence; The frequency deviation calculation formula is: ； Among them, foe is the frequency offset measurement result; theta is the phase difference of the autocorrelation sequence; LP is the length of the autocorrelation sequence; OP is the number of signal superpositions of the autocorrelation sequence; and fs is the sampling frequency of the transmission signal.

8. A synchronization device based on double correlation in UAV and satellite communication, characterized in that: Applied to a receiving end, the device includes: A transmission signal receiving module is used to receive a transmission signal during communication between the UAV and the satellite, wherein the synchronization header of the transmission signal includes a ZC sequence and an M sequence; A local sequence acquisition module is used to obtain local ZC sequences and local M sequences; A coarse synchronization capture module, configured to perform coarse synchronization capture on the ZC sequence in the transmission signal based on the local ZC sequence to obtain a plurality of position ambiguity points; a mutual correlation sequence calculation module, configured to use the plurality of position ambiguity points as starting positions, and conjugate-multiply the local M sequence with the M sequences of the transmission signals at different starting positions to obtain a mutual correlation sequence; An autocorrelation sequence calculation module is used to perform autocorrelation conjugate multiplication and sum the cross-correlation sequences to obtain an autocorrelation sequence; The frequency offset measurement result calculation module is used to perform frequency offset measurement based on the autocorrelation sequence to obtain a frequency offset measurement result.

9. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The electronic device comprises a processor, a memory and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

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